GitHub Copilot
GitHub Copilot is an AI-powered coding companion that helps developers write, debug, and refactor code faster than ever. Built directly into popular IDEs like VS Code, JetBrains, and Visual Studio, Copilot suggests context-aware code completions and automates repetitive tasks. With Agent Mode, Copilot can plan, write, test, and even submit pull requests—acting like an onboarded team member that understands your repositories. Developers can toggle between advanced models such as GPT-5, Claude Opus 4.1, and Gemini 2.5 Pro to balance speed and depth. Its Copilot Chat and Spaces features bring code, documentation, and project notes together for richer, team-tailored insights. Whether you’re building solo or leading an enterprise project, Copilot enhances productivity and creativity across the entire software lifecycle.
The GitHub Copilot coding agent streamlines development by automating repetitive and time-consuming tasks, allowing developers to focus on more complex coding.
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Devstral Small 2
Devstral Small 2 is the compact, 24 billion-parameter variant of the new coding-focused model family from Mistral AI, released under the permissive Apache 2.0 license to enable both local deployment and API use. Alongside its larger sibling (Devstral 2), this model brings “agentic coding” capabilities to environments with modest compute: it supports a large 256K-token context window, enabling it to understand and make changes across entire codebases. On the standard code-generation benchmark (SWE-Bench Verified), Devstral Small 2 scores around 68.0%, placing it among open-weight models many times its size. Because of its reduced size and efficient design, Devstral Small 2 can run on a single GPU or even CPU-only setups, making it practical for developers, small teams, or hobbyists without access to data-center hardware. Despite its compact footprint, Devstral Small 2 retains key capabilities of larger models; it can reason across multiple files and track dependencies.
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Devstral 2
Devstral 2 is a next-generation, open source agentic AI model tailored for software engineering: it doesn’t just suggest code snippets, it understands and acts across entire codebases, enabling multi-file edits, bug fixes, refactoring, dependency resolution, and context-aware code generation. The Devstral 2 family includes a large 123-billion-parameter model as well as a smaller 24-billion-parameter variant (“Devstral Small 2”), giving teams flexibility; the larger model excels in heavy-duty coding tasks requiring deep context, while the smaller one can run on more modest hardware. With a vast context window of up to 256 K tokens, Devstral 2 can reason across extensive repositories, track project history, and maintain a consistent understanding of lengthy files, an advantage for complex, real-world projects. The CLI tracks project metadata, Git statuses, and directory structure to give the model context, making “vibe-coding” more powerful.
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Cody
Cody, Sourcegraph’s AI code assistant goes beyond individual dev productivity, helping enterprises achieve consistency and quality at scale with AI.
Unlike traditional coding assistants, Cody understands the entire codebase, enabling deeper contextual awareness for smarter autocompletions, refactoring, and AI-driven code suggestions. It integrates with IDEs like VS Code, Visual Studio, Eclipse, and JetBrains, providing inline editing and chat without disrupting workflows. Cody also connects with tools like Notion, Linear, and Prometheus to enhance development context. Powered by advanced LLMs like Claude Sonnet 4 and GPT-4o, it optimizes speed and performance based on enterprise needs, and is always adding the latest AI models. Developers report significant efficiency gains, with some saving up to six hours per week and doubling their coding speed.
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